Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling | Paper Citation Record

Observation ec1076e9-3efa-4774-9fed-e90f88a1acfc · outbound

This paper cites Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas.Solar Energy, 70(3):295–310, 2001.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas.Solar Energy, 70(3):295–310, 2001

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This paper cites GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

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This paper cites Bruinsma, Tom R.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Bruinsma, Tom R

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This paper cites Deep Learning for Day Forecasts from Sparse Observations.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Deep Learning for Day Forecasts from Sparse Observations

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This paper cites Enhancing a high resolution data-driven weather prediction model with surface descriptors.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Enhancing a high resolution data-driven weather prediction model with surface descriptors

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This paper cites Configuration and in- tercomparison of deep learning neural models for statistical downscaling.Geoscientific Model Development, 13(4):2109–2124, 2020.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Configuration and in- tercomparison of deep learning neural models for statistical downscaling.Geoscientific Model Development, 13(4):2109–2124, 2020

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This paper cites Bruinsma, Ana Lucic, Megan Stanley, Anna Allen, Johannes Brand- stetter, Patrick Garvan, Maik Riechert, Jonathan A.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Bruinsma, Ana Lucic, Megan Stanley, Anna Allen, Johannes Brand- stetter, Patrick Garvan, Maik Riechert, Jonathan A

Reference 7

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This paper cites Autoregressive Conditional Neural Processes.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Autoregressive Conditional Neural Processes

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This paper cites Neural diffusion processes.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Neural diffusion processes

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This paper cites Environmental lapse rate for high-resolution land surface downscaling: An application to ERA5.Earth and Space Science, 7(5):e2019EA000984, 2020.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Environmental lapse rate for high-resolution land surface downscaling: An application to ERA5.Earth and Space Science, 7(5):e2019EA000984, 2020

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This paper cites Copernicus Digital Elevation Model: GLO-30,.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Copernicus Digital Elevation Model: GLO-30,

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Observation 109b88d1-6116-42a6-8989-b6b3c8ac1860 · outbound

This paper cites Farr, Paul A.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Farr, Paul A

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This paper cites Lisaius, Markus Immitzer, Toby Jackson, James Ball, David A.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Lisaius, Markus Immitzer, Toby Jackson, James Ball, David A

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This paper cites TESSERA v2: Scaling Pixel-wise Earth Foundation Models.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling TESSERA v2: Scaling Pixel-wise Earth Foundation Models

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Unresolved cited work

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Unresolved cited work

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Observation abca4824-faed-4de6-bc31-51144e92b259 · outbound

This paper cites Rezende, and S.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Rezende, and S

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Unresolved cited work

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This paper cites Genton, and Eric Aldrich.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Genton, and Eric Aldrich

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This paper cites Bruinsma, Andrew Y.

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Bruinsma, Andrew Y

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Development of temperature patterns during clear nights.Journal of Applied Meteorology, 37(6):559–571, 1998

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Unresolved cited work

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Unresolved cited work

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling The ERA5 global reanalysis.Quarterly Journal of the Royal Meteorological Society, 146(730):1999–2049, 2020

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling A comparative study of convolutional neural network models for wind field downscaling.Meteorological Ap- plications, 27(6):e1961, 2020

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Learning dynamics in linear VAE: Posterior collapse threshold, superfluous latent space pitfalls, and speedup with KL annealing

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Innovative short-term weather forecasting system combining data-driven and dynamic down- scaling approaches.Artificial Intelligence for the Earth Systems, 4(3), 2025

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Auto-Encoding Variational Bayes

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling A high-resolution canopy height model of the Earth.Nature Ecology & Evolution, 7(11):1778–1789, 2023

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Decoupled weight decay regularization

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Terrain tiles

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Cambridge University Press, Cambridge, 2018

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Residual corrective diffusion modeling for km- scale atmospheric downscaling.Communications Earth & Environment, 6:124, 2025

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Marinescu, Susan C

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Menne, Simon Noone, Nancy W

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Unresolved cited work

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling On the difficulty of training recurrent neural networks

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling de Sousa, Niels H

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Gibson, Jorge Baño-Medina, Gab Abramowitz, Tom Beucler, Jose González-Abad, William Chapman, Paula Harder, and José Manuel Gutiér- rez

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling WeatherBench 2: A benchmark for the next generation of data-driven global weather models.Journal of Advances in Modeling Earth Systems, 16(6):e2023MS004019, 2024

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling A simple height-based correction for temperature downscaling in complex terrain.Meteorological Applications, 17(3): 329–339, 2010

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Theobald, Dylan Harrison-Atlas, William B

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Stellar initial mass function variation in massive early-type galaxies: the potential role of the deuterium abundance

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Scott Hosking, and Richard E

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Taylor, and John L

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Statistical downscaling of gridded wind speed data using local topography.Journal of Hydrometeorology, 18(2):335–348, 2017

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Local Off-Grid Weather Forecasting with Multi-Modal Earth Observation Data

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Dynamical global downscaling of global reanalysis

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling ESA WorldCover 10 m 2021 v200, 2022

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling Unresolved cited work

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Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling GLO-30 global digital surface model

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